def test_enable_eager_for_tf_1(self, mock_eager_execution, mock_is_tf_v1): mock_is_tf_v1.return_value = False utils.enable_eager_for_tf_1() # Work around as assert_not_called is not supported in py35 self.assertFalse(mock_eager_execution.called) mock_is_tf_v1.return_value = True utils.enable_eager_for_tf_1() mock_eager_execution.assert_called_once_with()
# See the License for the specific language governing permissions and # limitations under the License. """End to end integration test for cloud_fit.""" import os from typing import Text import uuid from absl import logging import numpy as np import tensorflow as tf from tensorflow_cloud.tuner import cloud_fit_client as client from tensorflow_cloud.tuner import cloud_fit_utils as utils from tensorflow_cloud.utils import google_api_client # Can only export Datasets which were created executing eagerly utils.enable_eager_for_tf_1() MIRRORED_STRATEGY_NAME = utils.MIRRORED_STRATEGY_NAME MULTI_WORKER_MIRRORED_STRATEGY_NAME = utils.MULTI_WORKER_MIRRORED_STRATEGY_NAME # The staging bucket to use to copy the model and data for remote run. _REMOTE_DIR = os.path.join("gs://", os.environ["TEST_BUCKET"]) # The project id to use to run tests. _PROJECT_ID = os.environ["PROJECT_ID"] # The GCP region in which the end-to-end test is run. _REGION = os.environ["REGION"] # The base docker image to use for remote environment. _DOCKER_IMAGE = os.environ["DOCKER_IMAGE"]